Tadesse et al. combined two models, LSTM and CNN, to explore the potential of each algorithm separated and their combined model applied in classifying the sentences with suicidal and non-suicidal content. The proposed algorithm was compared with CNN, LSTM separated and other machine learning classifiers such as SVM, NB, RF, and XGBoost. They found the proposed model improved the accuracy with \(93.8\%\) , F1-score \(93.4\%\) , recall \(94.1\%\)  and Precision \(93.2\%\)  [1]}.
